ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012 A Simple Robust Digital Image Watermarking against  ...
ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 20121. Without encoding of watermark.                    ...
ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012In this paper m=3 is chosen and corresponding code is...
ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012image.                                               ...
ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012table V &VI and Fig. 4 & Fig. 5 that as noise density...
ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012  TABLE VII. MSE BETWEEN WATERMARKED IMAGE AND SALT A...
ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012                  TABLE IX. PICTORIAL COMPARISON OF E...
ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012                           REFERENCES                ...
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A Simple Robust Digital Image Watermarking against Salt and Pepper Noise using Repetition Codes

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In this paper a robust, spatial domain watermarking
scheme using simple error control coding technique is
proposed. The idea of this scheme is to embed an encoded
watermark using (5,1) repetition code inside the cover image
pixels by LSB (Least Significant Bit) embedding technique.
The proposed algorithm is simple, more robust against Salt
and Pepper Noise than LSB only watermarking techniques.
In this paper comparison is made between embedding different
watermark encoding schemes such as (7, 4) Hamming code,
(3, 1) repetition code, (5,1) repetition code and without
encoding for different noise density of salt and pepper noise.
Result shows watermark encoding scheme using (5,1)
repetition code provides better robustness towards random
error compared to other said scheme, without much
degradation in cover image.

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Transcript of "A Simple Robust Digital Image Watermarking against Salt and Pepper Noise using Repetition Codes"

  1. 1. ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012 A Simple Robust Digital Image Watermarking against Salt and Pepper Noise using Repetition Codes Mr. Rohith.S1, Dr. K.N.hari bhat2 1,2 Nagarjuna College of Engineering and Technology, Bengaluru, Karnataka, India. Email: rohithvjp2006@gmail.com, knhari.bhat@gmail.comAbstract­—In this paper a robust, spatial domain watermarking watermarking, error control coding techniques and salt andscheme using simple error control coding technique is pepper noise are discussed in section 1V. Proposed schemeproposed. The idea of this scheme is to embed an encoded is described in section V. In section VI Performance analysiswatermark using (5,1) repetition code inside the cover image is illustrated. Conclusions are discussed in section VII.pixels by LSB (Least Significant Bit) embedding technique.The proposed algorithm is simple, more robust against Saltand Pepper Noise than LSB only watermarking techniques. II. RELATED WORKSIn this paper comparison is made between embedding different In spatial domain, LSB substitution technique[5,6] canwatermark encoding schemes such as (7, 4) Hamming code, be used to embed the secret data in cover image. In LSB(3, 1) repetition code, (5,1) repetition code and without technique 1 bit of secret message replaces the least significantencoding for different noise density of salt and pepper noise.Result shows watermark encoding scheme using (5,1) bit of cover image pixel. LSB technique is relatively simplerepetition code provides better robustness towards random and has low computational complexity [3].error compared to other said scheme, without much A spiral based LSB approach for hiding message in imagesdegradation in cover image. was proposed in [16]. They used LSB substitution technique to embed the watermark and order of insertion of watermarkIndex Terms—LSB Watermarking, Repetition code, Hamming based on spiral substitution algorithm. In [13] 3rd and 4th LSBcode, Salt and Pepper noise Substitution technique was proposed. They used 3rd and 4th LSB bit position of cover image pixel to embed two watermark I. INTRODUCTION bits. This technique may increase the storage capacity to In recent years the growth of Internet and multimedia accommodate the watermark bits, but results decrease insystems has created the need of the copyright protection for perceptual quality of watermarked image. A Reversiblevarious digital medium (Ex: images, audio, video, etc.). To watermarking technique in spatial domain with error controlprotect the digital medium (Images) from illegal access and coding technique was discussed in [12]. They initiallyunauthorized modification Digital Image watermarking is used. encrypted the watermark and then encoded using errorIt is a branch of information hiding, which hides ownership control coding technique. This encoded watermark wasinformation inside the cover image. Watermarking can be embedded in the cover image using reversible watermarkingbroadly classified in to visible or invisible watermarking [1, technique. Results show that improvement in robustness by2]. Generally invisible watermarking is used in digital encoding watermark using (15,5) BCH code compared to (7,4)multimedia communication systems. Hamming code, (15,3) and (15,5) RS codes in a random error Watermark embedding can be in spatial or transformed channel where watermarked image was corrupted by Salt anddomain. In spatial domain watermarking, watermark bits pepper noise. But Watermark encoding and decodingdirectly alter the cover image pixels. Where as in transformed processes are complex. In [15] application of channel codingdomain watermarking cover image is transformed into in the spatial domain watermarking system for copyrightfrequency domain and then watermark bits are embedded [3]. protection of images was proposed. They used turbo codeOnce watermark embedding is done watermarked images are to encode the binary watermark and embedded in cover imageundergone wide verity of distortion during processing, directly by altering the pixel values. The scheme shows usingtransmission, storage, compression and reproduction, which turbo code provides better performance than encodingmay result in visual quality degradation of the watermarked watermark using BCH code. A variable block size basedimage [4]. This degradation in turn affects the visual quality adaptive watermarking in spatial domain was proposed [14].of the watermark. It may be necessary for identification of In this scheme cover image was divided into blocks, andownership. then watermark bit was embedded by altering the brightness This paper discusses how distortion in watermark can be value of the pixel. This may affect the perceptibility of thereduced and robustness against salt and pepper noise can watermarked image.be improved by simple watermarking and error control coding In this paper LSB replacement technique is used forscheme. The rest of the paper is organized as follows. In next embedding process and simple (n,1) repetition code wheresection related works are discussed. Section III describes n=3 and 5 are used for encoding the watermark. Robustnessrequirements of watermarking system. Basic concepts of LSB of watermark embedding scheme against salt and pepper noise is investigated for the cases© 2012 ACEEE 47DOI: 01.IJSIP.03.01.531
  2. 2. ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 20121. Without encoding of watermark. A. LSB Watermarking Scheme2. With (7,4) Hamming code for encoding watermark and The LSB watermarking is a simple replacement technique3. With proposed (3,1) and (5,1) repetition code for encoding used to embed watermark information in the cover image [5,watermark. 6]. In this technique if cover image is of 8-bit grayscale image and watermark is binary data then 1-bit of watermark replaces III. REQUIREMENTS OF WATERMARKING SYSTEM the LSB of cover image pixel as shown in the Table-I.For Ex: In this section, a number of watermarking system If cover image pixel is 153(10011001) and watermark bit is ‘0’requirements as well as the tradeoffs among them are then change in pixel value is 152(10011000). So by thisdiscussed. technique each LSB of the image pixel stores 1bit of theImperceptibility: The imperceptibility refers to the perceptual watermark. If cover image is 256X256 pixels, then it can storetransparency of the watermark in the cover image. Ideally, no 65536 bits or 8192bytes of watermark. Changing the LSB of aperceptible difference between the watermarked and original pixel results in small changes in the intensity of image. Theseimage should exist. changes cannot be perceived by the human visual system.Robustness: Robustness means ability to detect the However, a passive attacker can easily extract the changedwatermark in presence of common signal or image processing bits, since they can be recovered by very simple operation.attacks such as salt and pepper noise, Gaussian noise, channel To make watermark immune to noise and security to passivenoise, compression, geometrical attacks (cropping, scaling, attack one can insert watermark in higher order bits of therotation etc.), Random channel error etc. cover image. This may improve robustness and security, butCapacity: Watermarking capacity refers to the amount of distorts host image at large scale i.e perceptibility of thewatermark information that can be embedded into a host watermarked image decreases. For example if cover imageimage. Higher capacity implies that, more information can be pixel value is 153(10011001) and watermark bit ‘0’ is insertedembedded, but imperceptibility is poor. in to 4th LSB bit of cover image pixel value change is 145Blind watermarking: Original cover image or watermark is (10010001) if watermark bit is ‘1’ then no change in the pixelnot used in the process of watermark extraction. value. The change per pixel value is ‘8’ or no change. ImmunityImplementation Cost: Watermarking algorithm should be against passive attack can be obtained by encrypting thesimple, so that hardware implementation cost will reduce. watermark image before embedding [12].Processing Speed: Computation complexity of watermarking TABLE I. WATERMARK EMBEDDING USING LSB TECHNIQUEscheme decides processing speed of the algorithm so thattime delay will reduce. IV. WATERMARKING SCHEME The scheme aims to embed the encoded binary textpatterned watermark using simple error control coding schemesuch as repetition code inside the cover image pixel I(x, y)using LSB watermarking technique. Encoded watermark is B. Error Control Coding For Watermark Informationextracted simply collecting LSB bits from watermarked imageI’(x,y). Repetition decoding is applied to get back the original Transmission and storage may cause random errorwatermark W(m,n). The scheme is shown in the Fig. 1a and because of salt and pepper noise. To improve immunity1b. against this noise one can encode the watermark with error control coding scheme. Many simple and complex error control coding schemes are available [11]. Simple scheme is one in which computational complexity is less. In this paper Hamming code and repetition code are used for error control coding and LSB technique is used to embed encoded wate rmark. The performance of these schemes in presence of salt and pepper noise is investigated for different noise densities. Hamming Codes Figure 1a. Encoded Watermark Embedding Binary Hamming codes are class of linear block codes with single error correcting capability. In an (n,k) Hamming code where k is the number of bits in message word, n is the number of bits in the corresponding encoded word with n>k and (n-k) are the number of check bits. Hamming codes are characterized by n = 2m – 1 k= 2m - 1- m Where m=2, 3, 4, . . . Figure 1b. Watermark Extraction© 2012 ACEEE 48DOI: 01.IJSIP.03.01. 531
  3. 3. ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012In this paper m=3 is chosen and corresponding code is (7,4) In case of (3, 1) repetition code 1bit message is encoded intoblock code. In the encoding scheme 4 bits of watermark is 3 bits by repeating same message bit. Similarly (5, 1) repetitionencoded into block of 7 bits. A (7,4) systematic hamming code encodes 1bit message in to 5 bits by repeating samecode is given in [11] is characterized by generator matrix G message bit.Table-III illustrates (3,1) and (5,1) repetitionand is of the form given below. codes. G= [I4x4 : P4X3] (1) TABLE III. ENCODED DATA USING REPETITION CODESWhere sub matrices I4X4 is 4X4 Identity matrix and P4X3 is 4X3parity check matrix.One possible G matrix is (2) (2) In case of (3, 1) repetition code the decoder takes block of 3 bits at a time and counts the number of 1’s. If two or more bitsThe Encoded word V is given by are 1, then decoded bit is decided as 1. Otherwise, the decoder selects 0. So it can correct all patterns of one bit error. Similarly V1x7 = [d1X4 ] X [G4X7] (3) in (5, 1) repetition code, decoder takes 5 bits at a time andWhere d is message word counts the number of 1’s. If in the block of 5bits, three orThe set of all message words and corresponding code words more bits are 1, then the decoder selects 1 for the decodeddetermined using (3) is given in Table II bit. Otherwise, the decoder selects 0. So it can correct all TABLE II. SET OF ALL POSSIBLE 4-BIT MESSAGES AND CORRESPONDING7-BIT patterns of two bit errors. The coding scheme is simple but ENCODED WORD the number of cover image pixels affected are 3 and 5 times respectively than without coding. C. Salt and Pepper Noise attack Noise is undesired information that contaminates the image. Digital Images corrupted by Salt and pepper noise often occur in practice, due to faulty memory locations in hardware, channel decoder damages, dyeing down of signal in communication links, multi path wireless communication, transmission in noisy channel etc. [8, 9]. Salt and Pepper noise will alter the pixel value to either minimal (0) or maximal (255) for 8-bit gray scale image. In this type, based on noise density, image pixel values are randomly changed to either 0 or 255. MATLAB command “imnoise” is used to generate salt and pepper noise of various densities. V. PROPOSED SCHEME The proposed scheme uses (3,1) and (5,1) repetition codes for encoding watermark image and performance is compared with watermark image encoding using (7,4) Hamming code. A. Watermark Embedding and Extraction Algorithm In this section we discuss the watermark embedding and extraction algorithm. 8-bit Grayscale .bmp image of size 256x256 is used as a cover image, a binary text patterned image of sizeIn this case to accommodate all the encoded watermark bits 100x100 used as a watermark.in the cover image additional pixels used are ¾ times the Using (7,4) Hamming codeactual due to 3 check bits for every 4 bit message. In this section watermark encoding using (7,4) HammingRepetition codes codes, embedding and extraction process is discussed. Repetition codes are simplest type of linear block codes 1. The watermark is scanned row wise. The watermark bitin which single message bit is encoded into a block of identical sequence is divided into block of 4-bits and encoded it inton bits, producing (n,1) block code. This type of code allows block of 7 bits as explained in section IV.provision for a variable amount of redundancy and there are 2. To embed the encoded watermark bit, the LSB of each ofonly two types of code words possible. The generator matrix the cover image pixel is selected and replaced with each ofof a (n,1) repetition code is (1Xn) vector G1Xn=[11 1 1.....]. i.e. the encoded watermark bit. The procedure is repeated untilan all zeros code word or all ones code word[10]. all the watermark bits are filled. Obtained image is watermarked© 2012 ACEEE 49DOI: 01.IJSIP.03.01.531
  4. 4. ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012image. And I(x,y) is value of (x,y)th watermarked image pixel.3. To extract the encoded watermark bits, LSBs of watermarked I’(x,y) is value of (x,y)th noise added watermarked image pixel.image pixels where watermark bits are embedded are collected. M, N is size of the watermarked image.(7,4) decoding and correcting technique are applied to get SNR and MSE as given by (6) and (7) give the effect of saltback the extracted watermark bit sequence. and pepper noise on watermarked imageUsing (3,1) and (5,1) Repetition code Robustness between original watermark and extracted Watermark encoding scheme using Repetition codes, watermark is measured in terms of Bit Error Rate (BER)Embedding and Extraction algorithm is discussed. computed using (8) and Normalized Correlation (NC)1. Each bit is encoded into block of 3-bits using (3,1) repetition computed using (9).code. Same procedure is used in case of (5,1) repetition codeexcept 1 bit is encoded in to 5-bits.2. In embedding process using (3,1) repetition code LSB ofthree consecutive pixels of cover image are filled with Where W (i, j) is original watermark bit.corresponding single bit of watermark. For example first bit W’ (i, j) is extracted watermark bit.of watermark (0 or 1) is filled in LSB’s of first three pixels of M, N is size of the watermark.cover image next bit of watermark is filled in LSB of next three is Bit by bit modulo-2 addition (logical XOR)pixels of cover image etc. The procedure is repeated until all For computing Normalized Correlation(NC) binary 0 isthe bits are embedded. The image so obtained is called regarded as -1 and is given bywatermarked image. In case of encoding with (5,1) repetitioncode, blocks of five pixels of cover image are used and thefive LSB’s are filled with single bit of watermark image.3. To extract the encoded watermark bits, in case of (3,1)repetition code, LSB bits from block of three watermarked BER and NC values are generally 0 to 1. Ideally BER shouldimage pixels are collected in the same order. Decoding process be 0 and NC should be 1. Performance of proposed scheme isas explained earlier is applied to obtain extracted watermark. investigated using 256X256 pixels 8-bit gray scale cover imageIn case of (5,1) code block of 5 bits are considered. “lena.bmp “ and binary text patterned watermark of size 100X100 bits. They are shown in the Fig. 2a and Fig. 2b VI. PERFORMANCE ANALYSIS respectively. The effect of watermark in cover image and watermark immunity against salt and pepper noise for four The perceptual quality between cover image and different caseswatermarked image is measured using SNR (signal to Noise Case1. Without coding.Ratio) and MSE (Mean Square Error), as defined in (4) and (5) Case2. With (7,4) Hamming code.respectively. Larger SNR implies better quality of watermarked Case3. With (3,1) repetition code.image. The SNR and MSE are defined below. For cover image, Case4. With (5,1) repetition code are investigated The total number of cover image pixels used to embed the watermark and SNR of watermarked image computed usingWhere C(x,y) is decimal value of 8-bit pixel at location (4) for all four cases without considering the salt and pepper(x,y) of cover image. noise are given in table IV. In 1st case total numbers ofMSE is Mean square error and is given by watermark bits are 10000 so 10000 cover image pixels are used to embed all the bits. Case2 uses (7,4) Hamming codes so (7/ 4)(10000)=17,500 pixels are used to accommodate all the bits.Where M, N is size of the cover image. Similarly case3 and case4 (3,1) and (5,1) repetition codes areC’(x,y) is value of (x,y)th watermarked image pixel. used so 3X10000=30000 and 5X10000=50000 cover image pixelsSNR and MSE as defined by (4) and (5) give a measure of are used respectively in embedding process. It is shown inperceptibility of watermarked image. Larger the value of SNR table IV that increase in watermark bits increases the coverbetter the perceptibility. The SNR and MSE given in (4) and image pixels affected and hence reduces the SNR of(5) correspond to cover image and watermarked image without watermarked image. Even though there is reduction in SNR,any noise. The effect of noise on the extracted watermark can visual quality of the watermarked image is still acceptable inbe studied by computing SNR of watermarked image and all the cases as shown in Fig. 3. For all the four cases mentionednoisy watermarked image for different noise densities. In this above the BER in extracted watermark and NC betweencase SNR is defined as original and extracted watermark for different noise density of salt and pepper noise are computed and given in table V and VI respectively. A Plot of BER vs. Noise density and NC vs. Noise density are given in Fig. 5 and Fig. 6 respectively. InWhere table V BER ‘0’ indicates original and extracted watermark are identical. Similarly in table VI NC value ‘1’ indicates extracted watermark is same as original watermark. It is also observed in© 2012 ACEEE 50DOI: 01.IJSIP.03.01.531
  5. 5. ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012table V &VI and Fig. 4 & Fig. 5 that as noise density increases,(5,1) repetition code provides highest NC and minimal BERcompared to other three cases. SNR of noisy watermarkedimage and MSE between watermarked image and noisywatermarked image for different noise density are computedusing (7) and (8) respectively and given in table VII and VIII.For the four cases as noise density increases more number ofwatermarked pixels are affected by salt and pepper noise thisin turn affects the watermark. Effect of noise on watermarkedimage with noise density 0.4 for four different cases are givenin Fig. 4 Table IX is pictorial comparison of extracted watermarkwith different noise density values of four different cases. Itis seen that for all the 4 cases if NC is greater than 0.75 theextracted watermark is legible. For noise density 0.4, (5,1)provides high perceptual quality compared to other threecases. Comparing the four schemes it is seen that schemesemploying encoding of watermark image exhibits betterrobustness than without encoding, in the presence of saltand pepper noise amongst the schemes employing encoding,(7,4) Hamming code is capable of correcting single error in a Figure 3. Perceptibility measure of watermarked image for a.block of 7 bits. The number of pixels of cover image used for Without encoding b. with (7,4) Hamming code. c. (3,1) repetitionembedding encoded watermark is 17500 which is less compared code d. (5,1) repetition codeto 30000 as in case of (3,1) repetition code or 50000 as in case TABLE V. BIT ERROR RATE IN EXTRACTED WATERMARK IN PRESENCE OF SALT ANDof (5,1) repetition code. In case of (7,4) Hamming code the PEPPER NOISEwatermarked image perceptibility is highest since comparedto (3,1) or (5,1) repetition code least number of cover imagepixels are used for embedding. Even though perceptibility isgood robustness is poor. In case of (5,1) repetition code thewatermarked image perceptibility even though not as good asin the case of (7,4) Hamming code, it is still perceptible. Thescheme is more robust compared to the other three schemesdiscussed. Thus with marginal reduction in perceptibility ofwatermarked image it is possible to achieve better robustnessin the presence of salt and pepper noise. TABLE IV. T OTAL NUMBER OF COVER IMAGE PIXELS TABLE VI. N ORMALIZED CORRELATION BETWEEN ORIGINAL WATERMARK AND EXTRACTED WATERMARK IN PRESENCE OF SALT AND PEPPER NOISE Figure 2a. 256X256 gray scale cover image lena.bmp Figure 2b. 100X100 binary text patterned watermark© 2012 ACEEE 51DOI: 01.IJSIP.03.01. 531
  6. 6. ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012 TABLE VII. MSE BETWEEN WATERMARKED IMAGE AND SALT AND PEPPER NOISE ADDED WATERMARKED IMAGE TABLE VIII. SNR IN DB OF NOISY WATERMARKED IMAGE FOR DIFFERENT NOISE DENSITY Figure 5. Plot of Normalized Correlation between original and extracted watermark in presence of salt and pepper noise with different noise density Figure 6. Plot of Bit Error Rate in extracted watermark in presence of Salt and Pepper noise with different Noise DensityFigure 4. watermarked image in presence of salt and pepper noisewith noise density 0.4 for a. without coding b. with (7,4) hamming code c.(3,1) repetition code d. (3,1) repetition code© 2012 ACEEE 52DOI: 01.IJSIP.03.01.531
  7. 7. ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012 TABLE IX. PICTORIAL COMPARISON OF EXTRACTED WATERMARK WITH DIFFERENT NOISE DENSITY OF SALT AND PEPPER NOISE ing repetition codes is simple compared to (7,4) Hamming VII. CONCLUSION codes. So processing speed of the algorithm will increase. This algorithm is more suitable in noisy channels and stor- This paper discusses a simple, robust LSB watermarking age where watermark robustness against salt and pepperscheme against salt and pepper noise using repetition code. noise is needed. From Fig. 5 it is seen that for a given noiseIn this scheme watermark is encoded by (5,1) repetition code density NC is more and BER is less in case of (5,1) repetitionand embedding using LSB Technique. This scheme is tested code compared to (3,1) repetition code. Higher the ‘n’, betterwith Salt and Pepper noise for different noise density values the immunity against noise as seen in table IX. However per-and compared with embedding encoded watermark using ceptibility decreases with increases in n. this is because of(7,4)Hamming code, (3,1) repetition code and without encod- large number of pixels of cover image are affected in embed-ing. The experimental results and tabulation show that scheme ding watermark bits. At higher noise densities n has to beis simple and robust against Salt and Pepper Noise with dif- increased to obtain robustness but perceptual quality of theferent noise density. Using this scheme extracted watermark watermarked image or SNR will decrease.up to 0.4 noise density can be easily identified. Computa-tional complexity of watermark encoding and decoding us© 2012 ACEEE 53DOI: 01.IJSIP.03.01.531
  8. 8. ACEEE Int. J. on Signal & Image Processing, Vol. 03, No. 01, Jan 2012 REFERENCES [13]. Abdullah Bamatraf , Rosziati Ibrahim , Mohd. Najib B. Mohd Salleh ,”Digital watermarking algorithm using LSB” International[1]. Jianqin Zhou, Lingyun He, Cheng Shangguan “Watermarking Conference on Computer Applications and Industrial Electronics,Scheme Based on DCT and DHT” 2009 Second International 2010,PP-155 - 159Symposium on Electronic Commerce and Security 2009, Vol. 1,pp [14]. Somchok Kimpan, Attasit Lasakul, Sakreya Chitwong223 – 227 “Variable block size based adaptive watermarking in spatial domain”[2]. Vidyasagar M. Potdar, Song Han, Elizabeth Chang”A Survey IEEE International Symposium on Communications and Informationof Digital Image Watermarking Techniques”, 3rd IEEE International Technology, 2004. vol.1, pp 374 – 377Conference on Industrial Informatics (INDIN) 2005,pp-709-716. [15]. Rughooputh.H.C.S ,Bangaleea.R ,”Effect of channel coding[3]. Saba Riaz, M. Younus Javed, ,M. Almas Anjum “Invisible on the performance of spatial watermarking for copyrightWatermarking Schemes in Spatial and Frequency Domains” IEEE protection” IEEE AFRICON 2002, Africa. vol.1, pp-149- 153.International Conference on Emerging Technologies ,pp 211 – 216 [16]. Hassan Mathkour, Ghazy M.R. Assassa , Abdulaziz Al[4]. Saeid Fazli and Gholamreza Khodaverdi “Trade-Off between Muharib, Ibrahim Kiady “A Novel Approach for Hiding MessagesImperceptibility and Robustness of LSB Watermarking Using SSIM in Images”, International Conference on Signal Acquisition andQuality Metrics” Second International Conference on Machine Processing, 2009,pp-89 - 93Vision-2009,pp101– 104.[5]. C.K.Chan, L.M. Cheng.” Hiding data in images by simple LSB AUTHORSsubstitution” Pattern Recognition2004,pp469-474[6]. N. Nikolaidis and I. Pitas, “Robust Image Watermarking in the ROHITH S received B.E. degree inSpatial Domain,” Signal Processing, Vol. 66, No. 3, pp. 385-403, Electronics and CommunicationMay 1998. engineering in 2006 and M.Tech degree in[7]. V.Manimaran, R.Madhavan,”Image Watermarking Algorithms VLSI Design and Embedded systems inComparison & Analysis”, http://digitiallibrary.icett.org/pdf/364.pdf 2008 from Visvesvaraya Technological[8]. Salem Saleh Al-amri , N.V. Kalyankar, Khamitkar S.D “A University, Karnataka. He is currentlyComparative Study of Removal Noise from Remote Sensing Image” working as a Lecturer at Nagarjuna CollegeInternational Journal of Computer Science Issues, 2010, Vol. 7, pp- of Engineering and Technology, Bangaluru.33-36. His main area of interest includes Digital[9]. Geoffrine Judith.M.C1 and N.Kumarasabapathy “Study And Watermarking, Steganography, Error Control Coding, CryptographyAnalysis Of Impulse Noise Reduction Filters” An International and VLSI Design.Journal of Signal & Image Processing Vol.2, No.1, March 2011[10]. Simon haykin “Digital Communication” john wiley & K.N. Hari Bhat received the B.E. degreesons, 2005. with honours from Mysore University in[11]. Shu Lin, Daniel J. Costello, “Error Control Coding 1966. M.Tech and Ph.D. degrees inFundamentals and Applications”, Prentice Hall, 1983. Electronics and Communication Engineering[12]. Jagadish nayak, P. Subbanna Bhat,Rajendra Acharya U,M. from Indian Institute of Technology, KanpurSathish Kumar “Efficient storage and transmission of digital fundus in 1973 and 1986 respectively. He isimages with patient information using reversible watermarking currently working as Dean Academic andTechniques and error control codes” J med syst(2009)33:163-171. Head, Department of Electronics and Communication Engineering (P.G.) at Nagarjuna College of Engineering and Technology, Bangalore, India. He was with Karnataka Regional Engineering College, Suratkal (now known as National Institute of Technology, Karnataka) for more than 30 years up to 2001. He has coauthored three books in the area of Communication. His areas of interest are Analog and Digital communication and Cryptography.© 2012 ACEEE 54DOI: 01.IJSIP.03.01.531

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